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   "pygments_lexer": "ipython3",
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 "nbformat": 4,
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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import numpy as np\n",
    "import random"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "def CTV(a):\n",
    "    l=len(a)\n",
    "    b=np.zeros((l,1))\n",
    "    for i in range(l):\n",
    "        b[i]=int(a[i])\n",
    "    return b\n",
    "\n",
    "def ARK(a,b):\n",
    "    c=np.mod(a+b,2)\n",
    "    return c\n",
    "\n",
    "def SR(a):\n",
    "    b=a.copy()\n",
    "    t=b[9:12].copy()\n",
    "    b[9:12]=b[3:6]\n",
    "    b[3:6]=t\n",
    "    return b\n",
    "\n",
    "def RN(a):\n",
    "    t1=a[0:3].copy()\n",
    "    t2=a[3:6].copy()\n",
    "    b=np.vstack((t2,t1))\n",
    "    return b\n",
    "\n",
    "def MC(a):\n",
    "    A=np.eye(3)\n",
    "    B=np.array([[0,1,0],[1,0,1],[1,0,0]])\n",
    "    M1=np.hstack((A,B))\n",
    "    M2=np.hstack((B,A))\n",
    "    M=np.vstack((M1,M2))\n",
    "    a[0:6]=np.mod(np.dot(M,a[0:6]),2)\n",
    "    a[6:12]=np.mod(np.dot(M,a[6:12]),2)\n",
    "    b=a\n",
    "    return b\n",
    "\n",
    "def SB(a):\n",
    "    l=len(a)\n",
    "    b=np.zeros((l,1))\n",
    "    A=np.array([[1,0,1],[1,1,0],[0,1,1]])#S盒中的仿射变换\n",
    "    s=np.array([[1],[0],[1]])\n",
    "    for i in range(int(l/3)):\n",
    "        b[3*i+2]=np.mod(a[3*i+1]+a[3*i]+a[3*i+2]+a[3*i+1]*a[3*i],2)\n",
    "        b[3*i+1]=np.mod(a[3*i+2]*a[3*i+1]+a[3*i],2)\n",
    "        b[3*i]=np.mod(a[3*i+2]*a[3*i]+a[3*i+1]+a[3*i],2)\n",
    "        b[3*i:3*i+3]=np.mod(np.dot(A,b[3*i:3*i+3])+s,2)\n",
    "    return b"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "#GF(2^3)上的不可约多项式为x^3+x+1\n",
    "def Ss_AES():\n",
    "    data = np.zeros((2**12, 12))\n",
    "    R1=np.zeros((6,1))\n",
    "    R1[0]=1\n",
    "    R2=np.zeros((6,1))\n",
    "    R2[1]=1 #子秘钥生成过程中的两个已知比特串\n",
    "    #P=CTV('{:012b}'.format(random.randint(0,2**12-1)))\n",
    "    P=CTV('{:012b}'.format(100))\n",
    "    for j in range(2**12):\n",
    "        K=CTV('{:012b}'.format(j))\n",
    "        C=MC(SR(SB(ARK(P,K))))\n",
    "        K1=np.mod(K[0:6]+R1+SB(RN(K[6:12])),2)\n",
    "        K2=np.mod(K1+K[6:12],2)\n",
    "        K=np.vstack((K1,K2))\n",
    "        C=SR(SB(ARK(C,K)))\n",
    "        K1=np.mod(K[0:6]+R2+SB(RN(K[6:12])),2)\n",
    "        K2=np.mod(K1+K[6:12],2)\n",
    "        K=np.vstack((K1,K2))\n",
    "        C=ARK(C,K)\n",
    "        data[j,:]=C.T\n",
    "    return data"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "# f is a function; x0 is a N-dimention row vector; xerr is a const\n",
    "def NM(f,x0,xerr):\n",
    "    N=len(x0)\n",
    "    times=0\n",
    "    x=np.zeros((N+1,N))\n",
    "    y=np.zeros(N+1)\n",
    "    x[0,:]=x0.copy()\n",
    "    for ii in range(N):\n",
    "        x[ii+1,:]= x[0,:].copy()\n",
    "        if x[0,ii]==0:\n",
    "            x[ii+1,ii]=0.5\n",
    "        else:\n",
    "            x[ii+1,ii]=1.5*x[0,ii]\n",
    "    for ii in range(N+1):\n",
    "        b=x[ii,:].copy()\n",
    "        y[ii]=f(b)\n",
    "        times=times+1\n",
    "    for kk in range(10000):   \n",
    "        order=sorted(range(len(y.T)),key=lambda g: y[g])\n",
    "        x=x[order,:]\n",
    "        y=y[order]\n",
    "        print(x[N,:])\n",
    "        print(y[0])\n",
    "        if np.linalg.norm(x[N,:]-x[0,:])< xerr:\n",
    "            break\n",
    "        m=np.mean(x[0:N,:],0)\n",
    "        r=2*m-x[N,:]\n",
    "        f_r=f(r)\n",
    "        times=times+1\n",
    "        if y[0] <= f_r and f_r < y[N-1]:\n",
    "            x[N,:]=r\n",
    "            y[N]=f_r\n",
    "            continue\n",
    "        elif f_r<y[0]:\n",
    "            s=m+2*(m-x[N,:])\n",
    "            f_s=f(s)\n",
    "            times=times+1\n",
    "            if f(s)<f_r:\n",
    "                x[N,:]=s\n",
    "                y[N]=f_s\n",
    "            else: \n",
    "                x[N,:]=r\n",
    "                y[N]=f_r\n",
    "            continue\n",
    "        elif f_r<y[N]:\n",
    "            c1=m+(r-m)*0.5\n",
    "            f_c1=f(c1)\n",
    "            times=times+1\n",
    "            if f(c1)<f_r:\n",
    "                x[N,:]=c1\n",
    "                y[N]=f_c1\n",
    "                continue\n",
    "        else:\n",
    "            c2=m+(x[N,:]-m)*0.5\n",
    "            f_c2=f(c2)\n",
    "            times=times+1\n",
    "            if f_c2<y[N]:\n",
    "                x[N,:]=c2\n",
    "                y[N]=f_c2\n",
    "                continue\n",
    "        for jj in range(1,N+1):\n",
    "            x[jj,:]=x[0,:]+(x[jj,:]-x[0,:])*0.5\n",
    "            y[jj]=f(x[jj,:])\n",
    "            times=times+1\n",
    "    return x[0,:],y[0],times"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "e0=[[1],[0]]\n",
    "e1=[[0],[1]]\n",
    "data=Ss_AES()\n",
    "n=np.size(data,1)\n",
    "key=random.randint(0,2**n)\n",
    "cipher=data[key,:]\n",
    "Ss=np.zeros((2**n,2**n))\n",
    "for i in range(2**n):\n",
    "    ds=1\n",
    "    for j in range(n):\n",
    "        if data[i,j]==0:\n",
    "            ds=np.kron(ds,e0)\n",
    "        else:\n",
    "            ds=np.kron(ds,e1)\n",
    "    Ss[:,i]=ds.T"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "g=nx.random_regular_graph(11,12,seed=7)\n",
    "list(g)\n",
    "nx.draw(g,with_labels=True,font_weight='bold')"
   ],
   "outputs": [
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     "output_type": "display_data",
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"
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "Sz=[[1,0],[0,-1]]\n",
    "Si=[[1,0],[0,1]]\n",
    "def addzz(t1,t2):\n",
    "    u=1\n",
    "    for ii in range(n):\n",
    "        if ii==t1 or ii==t2:\n",
    "            u=np.kron(u,Sz)\n",
    "        else:\n",
    "            u=np.kron(u,Si)\n",
    "    return u"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "cf=0\n",
    "for i,j in list(g.edges):\n",
    "    if cipher[i]==cipher[j]:\n",
    "        cf=cf-addzz(i,j)\n",
    "    else:\n",
    "        cf=cf+addzz(i,j)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "def sortdis(M,C):\n",
    "    P=np.abs(M)**2\n",
    "    PP=np.zeros(2**n)\n",
    "    for i in range(len(M)):\n",
    "        basis=np.zeros(len(M))\n",
    "        basis[i]=1\n",
    "        PP[i]=np.real(np.dot(np.dot(basis,C),basis.T))\n",
    "    index= np.array(PP).argsort()\n",
    "    P=P[index]\n",
    "    return P"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "source": [
    "from qiskit import QuantumCircuit, assemble, Aer\n",
    "from math import pi, sqrt\n",
    "from qiskit.visualization import plot_bloch_multivector, plot_histogram\n",
    "sim = Aer.get_backend('aer_simulator')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "def costfunction(x):\n",
    "    qc = QuantumCircuit(12)\n",
    "    initial_state = [1,0]\n",
    "    for qubit in range(12):\n",
    "        qc.initialize(initial_state, qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.h(qubit)\n",
    "    for qubit in range(12):\n",
    "        qc.ryy(x[qubit],qubit,np.mod(qubit+1,12)+int((qubit+1)/12))\n",
    "    for qubit in range(12):\n",
    "        qc.rx(x[qubit+12],qubit)\n",
    "    qc.save_statevector()\n",
    "    qobj = assemble(qc)\n",
    "    state = sim.run(qobj).result().get_statevector()\n",
    "    ampli=np.abs(state)\n",
    "    state1=ampli*Ss\n",
    "    state2=np.sum(state1,1)\n",
    "    state3=state2/np.sqrt(np.sum(np.abs(state2)**2))\n",
    "    ff=np.real(np.dot(np.dot(state3,cf),state3.T))\n",
    "    return ff"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "source": [
    "para=np.ones(24)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "source": [
    "output=NM(costfunction,para,0.1)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.3051368184409283\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.3051368184409283\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.5 1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.5 1.  1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.5 1.  1. ]\n",
      "-0.39426267709428525\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1.5]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.5 1. ]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.5 1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.4877507944029667\n",
      "[1.04166667 1.04166667 1.04166667 1.04166667 1.04166667 1.04166667\n",
      " 0.5        1.04166667 1.04166667 1.04166667 1.04166667 1.04166667\n",
      " 1.04166667 1.04166667 1.04166667 1.04166667 1.04166667 1.04166667\n",
      " 1.04166667 1.04166667 1.04166667 1.04166667 1.04166667 1.04166667]\n",
      "-0.7068760227531905\n",
      "[1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.7068760227531905\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.7068760227531905\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.7068760227531905\n",
      "[1.06456389 1.06456389 0.97775834 1.06456389 1.06456389 1.06456389\n",
      " 0.94040256 1.06456389 0.89901545 1.06456389 1.06456389 1.06456389\n",
      " 1.06456389 1.06456389 1.06456389 1.06456389 1.06456389 0.97052454\n",
      " 0.52289723 0.96268793 1.06456389 1.06456389 1.06456389 1.06456389]\n",
      "-0.7068760227531905\n",
      "[1.05078125 1.05078125 1.05078125 1.05078125 1.05078125 1.05078125\n",
      " 0.953125   1.05078125 0.92057292 1.05078125 1.05078125 1.05078125\n",
      " 1.05078125 1.05078125 1.05078125 1.05078125 1.05078125 1.05078125\n",
      " 1.05078125 0.50911458 1.05078125 1.05078125 1.05078125 1.05078125]\n",
      "-0.7068760227531905\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.7068760227531905\n",
      "[1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.5 1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.9991680532340278\n",
      "[1.  1.5 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      " 1.  1.  1.  1.  1.  1. ]\n",
      "-0.9991680532340278\n",
      "[1.05501302 1.05501302 1.05501302 1.05501302 1.05501302 1.05501302\n",
      " 0.94921875 1.05501302 0.91395399 1.05501302 1.05501302 1.05501302\n",
      " 1.05501302 1.05501302 1.05501302 1.05501302 1.05501302 0.51334635\n",
      " 1.05501302 0.96820747 1.05501302 1.05501302 1.05501302 1.05501302]\n",
      "-0.9991680532340278\n",
      "[1.10004391 1.10004391 0.9655358  1.10004391 0.98543345 1.10004391\n",
      " 0.90765178 1.10004391 0.84352107 1.10004391 1.10004391 0.99424964\n",
      " 1.10004391 1.10004391 1.10004391 1.10004391 1.10004391 0.95432679\n",
      " 0.97588258 0.9421837  1.10004391 0.95898488 0.55837724 1.01323835]\n",
      "-0.9991680532340278\n",
      "[1.0757729  1.0757729  0.97389694 1.0757729  0.98896735 1.0757729\n",
      " 0.93005578 1.0757729  0.88148341 1.0757729  1.0757729  0.53410623\n",
      " 1.0757729  1.0757729  1.0757729  1.0757729  1.0757729  0.96540727\n",
      " 0.98173355 0.95621014 1.0757729  1.0757729  1.0757729  1.0757729 ]\n",
      "-0.9991680532340278\n",
      "[1.05959744 1.05959744 0.51793077 1.05959744 1.05959744 1.05959744\n",
      " 0.94498698 1.05959744 0.90678349 1.05959744 1.05959744 1.05959744\n",
      " 1.05959744 1.05959744 1.05959744 1.05959744 1.05959744 0.97279188\n",
      " 1.05959744 0.96555809 1.05959744 1.05959744 1.05959744 1.05959744]\n",
      "-0.9991680532340278\n",
      "[1.06994422 1.06994422 0.97590487 1.06994422 0.52827755 1.06994422\n",
      " 0.93543611 1.06994422 0.89060007 1.06994422 1.06994422 1.06994422\n",
      " 1.06994422 1.06994422 1.06994422 1.06994422 1.06994422 0.96806825\n",
      " 0.98313866 0.95957859 1.06994422 1.06994422 1.06994422 1.06994422]\n",
      "-0.9991680532340278\n",
      "[1.09234822 1.09234822 0.96818689 1.09234822 0.98655395 1.09234822\n",
      " 0.91475549 1.09234822 0.85555791 1.09234822 1.09234822 0.99469197\n",
      " 1.09234822 1.09234822 1.09234822 1.09234822 1.09234822 0.95784011\n",
      " 0.97773776 0.94663111 1.09234822 0.96213989 1.09234822 0.55068156]\n",
      "-0.9991680532340278\n",
      "[1.06770833 1.06770833 1.06770833 1.06770833 1.06770833 1.06770833\n",
      " 0.9375     1.06770833 0.00520833 1.06770833 1.06770833 1.06770833\n",
      " 1.06770833 1.06770833 1.06770833 1.06770833 1.06770833 1.06770833\n",
      " 1.06770833 1.06770833 1.06770833 1.06770833 1.06770833 1.06770833]\n",
      "-0.9991680532340278\n",
      "[1.12719703 1.12719703 0.9561818  1.12719703 0.98147991 0.58553036\n",
      " 0.88258736 1.12719703 0.8010508  1.12719703 1.12719703 0.99268892\n",
      " 1.12719703 1.12719703 1.12719703 1.12719703 1.12719703 0.94193053\n",
      " 0.96933682 0.92649166 1.03315768 0.94785288 1.02532107 1.0168314 ]\n",
      "-0.9991680532340278\n",
      "[1.11741264 1.11741264 0.95955243 1.11741264 0.98290453 1.11741264\n",
      " 0.8916191  1.11741264 0.81635458 1.11741264 1.11741264 0.99325131\n",
      " 1.11741264 1.11741264 1.11741264 1.11741264 1.11741264 0.94639741\n",
      " 0.97169552 0.93214614 1.03060709 0.9518642  1.02337329 1.01553668]\n",
      "-0.9991680532340278\n",
      "[1.07491428 1.16171984 0.94428901 1.16171984 0.97645334 1.05984387\n",
      " 0.85072015 1.16171984 0.74705359 0.62005317 1.16171984 0.99070461\n",
      " 1.16171984 1.16171984 1.16171984 1.06768048 1.16171984 0.92616978\n",
      " 0.96101446 0.90654061 1.04215707 0.93369953 1.03219351 1.02139965]\n",
      "-0.9991680532340278\n",
      "[1.1083809  1.1083809  0.96266378 1.1083809  0.98421957 1.1083809\n",
      " 0.89995609 1.1083809  0.83048115 1.1083809  1.1083809  0.99377044\n",
      " 1.1083809  1.1083809  1.1083809  1.1083809  1.1083809  0.95052069\n",
      " 0.97387279 0.93736567 0.56671423 0.95556695 1.02157535 1.01434155]\n",
      "-0.9991680532340278\n",
      "[1.05377137 1.16838183 0.8813052  1.16838183 0.92377216 1.03387372\n",
      " 1.34457062 1.16838183 0.62089281 1.06258756 1.07072558 0.94258829\n",
      " 1.16838183 1.16838183 1.16838183 1.0442205  1.0381735  0.85738215\n",
      " 0.90338802 0.83146551 1.01052162 0.86732377 0.9973666  0.98311533]\n",
      "-0.9991680532340278\n",
      "[0.60761318 1.14927985 0.94857447 1.14927985 0.97826462 1.0552405\n",
      " 0.86220322 1.14927985 0.76651101 1.14927985 1.14927985 0.99141964\n",
      " 1.14927985 1.14927985 1.14927985 1.06247429 1.14927985 0.93184903\n",
      " 0.96401335 0.91372979 1.03891422 0.93879957 1.02971708 1.01975352]\n",
      "-0.9991680532340278\n",
      "[1.13779678 1.13779678 0.95253028 1.13779678 0.97993657 1.05099123\n",
      " 0.87280297 1.13779678 0.7844717  1.13779678 1.13779678 0.99207966\n",
      " 1.13779678 1.13779678 1.13779678 0.59613012 1.13779678 0.93709141\n",
      " 0.96678155 0.92036596 1.03592082 0.94350729 1.02743115 1.01823402]\n",
      "-0.9991680532340278\n",
      "[1.08115714 1.17519649 0.93964643 1.17519649 0.97449112 1.06483086\n",
      " 0.83828016 1.17519649 0.72597472 1.08839093 0.63352982 0.98992999\n",
      " 1.17519649 1.17519649 1.17519649 1.07332052 1.17519649 0.92001726\n",
      " 0.95776567 0.89875233 1.04567016 0.92817449 1.0348763  1.02318295]\n",
      "-0.9991680532340278\n",
      "[1.12313097 1.12313097 0.95758252 1.12313097 0.98207194 1.12313097\n",
      " 0.88634065 1.12313097 0.80741054 1.12313097 1.12313097 0.99292263\n",
      " 1.12313097 1.12313097 1.12313097 1.12313097 1.12313097 0.94378682\n",
      " 0.97031702 0.92884147 1.12313097 0.06063097 1.12313097 1.12313097]\n",
      "-0.9991680532340278\n",
      "[1.11726603 1.26298315 0.89799047 1.1689438  0.95198347 1.09196792\n",
      " 0.85128567 1.17617759 0.56689901 1.12847504 1.13882182 0.97590652\n",
      " 0.72131648 1.26298315 1.26298315 1.10512294 1.09743471 0.86757441\n",
      " 0.92606683 0.83462368 1.06227778 0.88021431 1.04555233 1.02743309]\n",
      "-0.9991680532340278\n",
      "[1.09991899 1.22408032 0.91308063 0.68241365 0.9590865  1.0783632\n",
      " 0.87328484 1.22408032 0.63096721 1.10946986 1.11828605 0.97947064\n",
      " 1.22408032 1.22408032 1.22408032 1.08957221 1.08302129 0.88716399\n",
      " 0.93700369 0.85908763 1.05306509 0.89793409 1.03881382 1.02337494]\n",
      "-1.5931636134792888\n",
      "[1.05709398 1.2149542  0.91358481 1.11307823 0.87803787 1.0296877\n",
      " 0.90345671 1.12091484 0.64020719 1.06923708 1.08044609 0.90395451\n",
      " 1.12814864 1.2149542  1.2149542  1.04393897 1.03561005 0.88847069\n",
      " 1.43676707 0.86126373 0.99752337 0.80028795 0.97940414 0.95977497]\n",
      "-1.5931636134792888\n",
      "[1.10824557 1.24275368 0.90583735 1.15594812 0.95567705 1.08489347\n",
      " 0.86272524 0.70108701 0.60021447 1.11859235 1.12814322 0.97775986\n",
      " 1.24275368 1.24275368 1.24275368 1.09703656 1.08993973 0.87776099\n",
      " 0.93175399 0.84734494 1.05748718 0.88942859 1.0420483  1.02532286]\n",
      "-1.5931636134792888\n",
      "[1.07140269 1.24241792 0.82912886 1.13205229 0.87742523 1.04171254\n",
      " 0.88659524 1.14054195 0.59528592 1.08455771 1.0967008  0.90550159\n",
      " 1.14837857 1.24241792 1.24241792 1.05715142 1.04812843 0.7946881\n",
      " 0.94104853 1.34418284 1.00686786 0.79319615 0.98723869 0.96597375]\n",
      "-1.5931636134792888\n",
      "[1.10389165 1.35898021 0.7479838  1.24412117 0.82220137 1.0352443\n",
      " 0.79428656 1.26375034 1.12293667 1.13430771 1.16238407 0.88212252\n",
      " 1.28186957 1.2522784  1.34728686 1.07094092 1.05007863 0.72381831\n",
      " 0.88916792 0.73037384 0.95467901 0.51697954 1.03882022 0.97492346]\n",
      "-1.5931636134792888\n",
      "[1.14415093 1.35257574 0.8488797  1.21806763 0.90774091 1.10796607\n",
      " 0.80905358 1.22841441 0.41739924 1.16018361 1.174983   0.94195897\n",
      " 1.23796528 1.22236741 0.81090908 1.1267822  1.11578543 0.80690503\n",
      " 0.9852818  0.86722674 1.06549911 0.80508672 1.04157606 1.01565942]\n",
      "-1.5931636134792888\n",
      "[1.08874534 1.27394601 0.81576739 1.19055548 0.87705992 1.03890565\n",
      " 0.83835391 1.20480675 0.36929012 1.11082816 1.1312123  1.41542623\n",
      " 1.21796176 1.19647783 1.26545635 1.06482229 1.04967574 0.87097214\n",
      " 0.99335662 0.88057909 0.98041323 0.64622024 1.04150186 0.92683629]\n",
      "-1.5931636134792888\n",
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      " 0.79314138 1.24744895 0.36884918 1.17353224 1.18956492 0.93712222\n",
      " 1.25779572 1.24089803 1.2951515  1.13734738 1.12543421 0.79081378\n",
      " 0.98405528 0.8561623  1.07095737 0.78884394 1.04504073 1.01696437]\n",
      "-1.5931636134792888\n",
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      " 0.82629791 1.22592567 0.2520195  1.10644017 1.13235681 0.96379807\n",
      " 1.24265112 1.21533618 1.3030363  1.04794775 1.02869025 0.8516882\n",
      " 0.98595155 0.86808625 0.94062906 0.65679109 1.01829787 1.45931624]\n",
      "-1.5931636134792888\n",
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      " 0.86608852 1.17247706 0.44373177 1.0857276  1.10454373 0.92288463\n",
      " 1.18462015 1.16478883 1.22846131 1.04326064 1.02927921 0.88846452\n",
      " 0.99786344 0.89934435 0.96534459 0.78706708 1.52173408 0.99601715]\n",
      "-1.5931636134792888\n",
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      " 0.83091618 1.20847225 0.40946978 1.12839582 1.14576456 0.87228497\n",
      " 1.21968126 1.20137542 1.26015002 1.08919556 1.07628962 1.30058971\n",
      " 0.92312912 0.87861774 1.01727305 0.71165017 0.98919669 0.95878063]\n",
      "-1.5931636134792888\n",
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      " 0.73720527 1.28469429 0.55470893 1.14363527 1.15448596 0.98363623\n",
      " 1.28469429 1.28469429 1.28469429 1.11914585 0.22219429 0.87002805\n",
      " 0.93136921 0.83547253 1.07421401 0.88328355 1.05667399 1.0376723 ]\n",
      "-1.5931636134792888\n",
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      " 0.81453662 1.23308298 0.29919893 1.13127285 1.15335567 0.91958742\n",
      " 1.24733425 1.22405999 1.29878672 1.08143316 1.0650244  0.85510255\n",
      " 0.90997267 0.86414956 0.98999001 0.6279476  1.05616935 0.93194833]\n",
      "-1.5931636134792888\n",
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      " 0.8418408  1.21564108 0.35391803 1.07541157 1.10582763 0.94792807\n",
      " 1.23527025 1.20321315 1.30613898 1.00676422 0.9841634  0.83142009\n",
      " 0.98085869 0.85524737 0.98268977 0.60092888 1.08233242 1.02230806]\n",
      "-1.5931636134792888\n",
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      " 0.81401254 1.2363311  0.26609892 1.12603679 1.14995985 0.89671091\n",
      " 1.25176998 1.22655619 1.30751015 1.07204379 1.05426764 0.85041238\n",
      " 0.98033428 0.86217664 0.97298038 0.58076777 1.04467467 0.91010189]\n",
      "-1.5931636134792888\n",
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      " 0.32712059 1.203167   0.38228592 1.22650648 1.15770828 0.98538352\n",
      " 1.2302035  1.18604922 1.32781546 1.06766264 1.02539722 0.88187439\n",
      " 1.05694832 0.93201981 1.06797431 0.55775784 1.133885   1.06073737]\n",
      "-1.5931636134792888\n",
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      " 0.81579939 1.2558767  0.20717413 1.17162656 1.11625854 0.93484651\n",
      " 1.28083346 1.24007567 1.37093681 1.00663441 0.96157318 0.79401634\n",
      " 0.98007312 0.82653087 1.47322322 0.50011536 1.10103705 1.02594225]\n",
      "-1.5931636134792888\n",
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      "  0.71396713  1.25917299 -0.63538638  1.2370044   1.18560345  1.03497922\n",
      "  1.36049856  1.06216286  1.28701842  1.13101685  0.82139522  0.95705899\n",
      "  1.06313607  0.96616439  1.11208275  0.69287809  1.1733673   1.07350964]\n",
      "-1.5931636134792888\n",
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      " 0.71449874 1.27377678 0.01150453 1.18648601 1.18104163 0.91952718\n",
      " 1.31101585 1.25019938 1.44546295 1.06652743 0.86337481 0.75647327\n",
      " 1.00867382 0.81931113 0.9509971  1.27540012 1.03039919 0.9173191 ]\n",
      "-1.5931636134792888\n",
      "[1.04599924 1.345374   0.82900721 1.21057416 0.88641962 1.0594733\n",
      " 0.82866087 1.23361117 0.30007786 1.08169587 1.1146466  0.94358874\n",
      " 1.25487611 1.22014758 1.33165056 1.0073279  0.98284368 0.81737176\n",
      " 0.97926358 0.84318465 0.98124726 0.56767295 1.08919345 1.02416707]\n",
      "-1.5931636134792888\n",
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      "  0.85616591  0.55835627  1.08006771 -0.04799557  1.29370505  0.88297724]\n",
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      "  1.04707291  0.30767433  0.99035112  0.09272978  1.33531872  0.82879287]\n",
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      "  0.92771864  0.72804983  0.95664326  0.0590662   1.17245519  0.89965767]\n",
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      "  1.01975362  0.76668516  0.93891042  0.13333122  1.20269678  0.88979931]\n",
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      "  0.94885055  0.67895831  0.95844473 -0.2598897   1.38725934  0.77814328]\n",
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      "  1.04011262  0.80269899  0.96080083  0.01352543  1.27090628  0.9753048 ]\n",
      "-2.592392705242742\n",
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      " 0.54662517 1.49378206 0.04143763 1.38771577 1.36629387 0.74083494\n",
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      " 0.9778441  0.62950979 0.99763488 0.16197179 1.22765213 0.81020709]\n",
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      "  1.01043263  0.78218671  0.94658069  0.30494534  1.1760423   0.71956327]\n",
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      "  0.59018463  0.7860797   0.98688862  0.13026227  1.35062349  0.78017142]\n",
      "-2.7210270127451963\n",
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      "  1.00990915  0.73829051  0.95339364  0.11050175  1.21656479  0.8847037 ]\n",
      "-2.7210270127451963\n",
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      "  1.12564534  0.77623601  0.92451774  0.03455817  1.29250067  0.6884029 ]\n",
      "-3.2280453787194516\n",
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      "-3.2280453787194516\n",
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      "-3.2280453787194516\n",
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      "-3.2280453787194516\n",
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      "-3.2280453787194516\n",
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      "-3.2280453787194516\n",
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      " 2.48617233 0.82133687 1.55805013 0.73123334 0.38764405 0.71014809\n",
      " 0.84275379 0.79047806 0.88809169 0.18563716 1.27948914 0.64992413]\n",
      "-3.2280453787194516\n",
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      "  1.00315974  0.71041337  1.01210816  0.15188956  1.31685991  0.79715606]\n",
      "-3.2280453787194516\n",
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      "  0.95431629  0.68535014  0.94761547 -0.08208775  1.34248335  0.57221716]\n",
      "-3.2280453787194516\n",
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      "  0.28208344  1.39087704 -0.13173477  1.39102797  1.51126234 -0.09242574\n",
      "  3.06485917  1.30368941  2.40679313  1.45214339 -0.15420987  0.46806978\n",
      "  0.69823886  0.7562545   0.65685154 -0.01411021  1.5192213  -0.05814151]\n",
      "-4.65671658310487\n",
      "[ 1.34994083e+00  1.88787328e+00  2.65717624e+00  1.54286238e+00\n",
      " -8.92283820e-02  1.16972416e+00  1.49534929e-01  1.37601580e+00\n",
      " -1.72026701e-01  1.41954255e+00  1.54149375e+00 -6.96522108e-02\n",
      "  3.02966854e+00  1.34017735e+00  2.44630618e+00  1.45232845e+00\n",
      " -2.26040325e-01  4.20585029e-01  7.36931652e-01  7.45933012e-01\n",
      "  6.72227630e-01 -6.74174481e-02  1.50697494e+00  2.20651144e-03]\n",
      "-4.65671658310487\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "output"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "qkey=np.zeros((2**n,1))\n",
    "qkey[key]=1\n",
    "qc = QuantumCircuit(12)\n",
    "initial_state = [1,0]\n",
    "for qubit in range(12):\n",
    "    qc.initialize(initial_state, qubit)\n",
    "for qubit in range(12):\n",
    "    qc.h(qubit)\n",
    "for qubit in range(12):\n",
    "    qc.ryy(output[0][qubit],qubit,np.mod(qubit+1,12)+int((qubit+1)/12))\n",
    "for qubit in range(12):\n",
    "    qc.rx(output[0][qubit+12],qubit)\n",
    "qc.save_statevector()\n",
    "qobj = assemble(qc)\n",
    "state = sim.run(qobj).result().get_statevector()\n",
    "fidelity=np.abs(np.dot(state,qkey))**2\n",
    "print(fidelity)\n",
    "ampli=np.abs(state)\n",
    "state1=ampli*Ss\n",
    "state2=np.sum(state1,1)\n",
    "state3=state2/np.sqrt(np.sum(np.abs(state2)**2))\n",
    "p=sortdis(state3,cf)\n",
    "plt.plot(range(2**12),p)"
   ],
   "outputs": [],
   "metadata": {}
  }
 ]
}